diff --git a/Orthtree/examples/Orthtree/octree_find_nearest_neighbor.cpp b/Orthtree/examples/Orthtree/octree_find_nearest_neighbor.cpp
index a6d53bd2f0d..f5c151749eb 100644
--- a/Orthtree/examples/Orthtree/octree_find_nearest_neighbor.cpp
+++ b/Orthtree/examples/Orthtree/octree_find_nearest_neighbor.cpp
@@ -46,7 +46,7 @@ int main(int argc, char** argv) {
   };
 
   for (const Point& p : points_to_find)
-    octree.nearest_neighbors
+    octree.nearest_k_neighbors
     (p, 1, // k=1 to find the single closest point
       boost::make_function_output_iterator
       ([&](const Point_set::Index& nearest)
@@ -57,7 +57,7 @@ int main(int argc, char** argv) {
 
   typename Octree::Sphere s(points_to_find[0], 0.0375);
   std::cout << std::endl << "Closest points within the sphere around " << s.center() << " with squared radius of " << s.squared_radius() << ":" << std::endl;
-  octree.nearest_neighbors
+  octree.neighbors_in_radius
   (s,
     boost::make_function_output_iterator
     ([&](const Point_set::Index& nearest)
diff --git a/Orthtree/include/CGAL/Orthtree.h b/Orthtree/include/CGAL/Orthtree.h
index ff0350c5206..5bb336a22c4 100644
--- a/Orthtree/include/CGAL/Orthtree.h
+++ b/Orthtree/include/CGAL/Orthtree.h
@@ -682,7 +682,7 @@ public:
   \warning Nearest neighbor searches requires `GeomTraits` to be a model of `CollectionPartitioningOrthtreeTraits`.
  */
   template<typename OutputIterator>
-  auto nearest_neighbors(const Point& query,
+  auto nearest_k_neighbors(const Point& query,
     std::size_t k,
     OutputIterator output) const -> std::enable_if_t<supports_neighbor_search, OutputIterator> {
     Sphere query_sphere(query, (std::numeric_limits<FT>::max)());
diff --git a/Orthtree/test/Orthtree/test_octree_nearest_neighbor.cpp b/Orthtree/test/Orthtree/test_octree_nearest_neighbor.cpp
index b0383ee2d26..2f37a75236c 100644
--- a/Orthtree/test/Orthtree/test_octree_nearest_neighbor.cpp
+++ b/Orthtree/test/Orthtree/test_octree_nearest_neighbor.cpp
@@ -71,7 +71,7 @@ void naive_vs_octree(std::size_t dataset_size) {
   auto octree_start_time = high_resolution_clock::now();
   {
     std::vector<Point_set::Index> k_neighbors;
-    octree.nearest_neighbors(random_point, 1, std::back_inserter(k_neighbors));
+    octree.nearest_k_neighbors(random_point, 1, std::back_inserter(k_neighbors));
     octree_nearest = get(points.point_map(), *k_neighbors.begin());
   }
   duration<float> octree_elapsed_time = high_resolution_clock::now() - octree_start_time;
@@ -121,7 +121,7 @@ void kdtree_vs_octree(std::size_t dataset_size, std::size_t K) {
   Octree octree(points, points.point_map());
   octree.refine(10, 20);
   auto octree_start_time = high_resolution_clock::now();
-  octree.nearest_neighbors(random_point, K, std::back_inserter(octree_nearest_neighbors));
+  octree.nearest_k_neighbors(random_point, K, std::back_inserter(octree_nearest_neighbors));
   duration<float> octree_elapsed_time = high_resolution_clock::now() - octree_start_time;
 
   std::cout << "Octree --> "