A KD-Tree, or k-dimensional tree, is a data structure used for organizing points in a k-dimensional space. It is particularly useful for tasks like nearest neighbor searches and range searches. The tree is built by recursively splitting the space into two halves based on the values of the points along different dimensions. Each node in a KD-Tree represents a point, and the tree structure allows for efficient querying. By dividing the space, it reduces the number of comparisons needed to find nearby points, making it faster than a simple list search, especially in higher dimensions.