A Ball Tree is a data structure used for organizing points in a multi-dimensional space. It is particularly useful for nearest neighbor searches and clustering tasks. The structure partitions the space into nested hyperspheres (or "balls"), allowing efficient querying of nearby points. In a Ball Tree, each node represents a ball that contains a subset of points. The tree is built recursively, where each node splits the points into two groups based on their distances from a chosen center point. This method helps reduce the number of distance calculations needed when searching for the nearest neighbors, making it faster than some other methods like k-d trees.