Build a KNeighborsClassifier which matches the scikit-learn API.

https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html

Technically there are 3 different strategies ‘ball_tree’, ‘kd_tree’, ‘brute’. This issue is only to support the "brute" method which checks the distance between the predicted point with every point in the input.

The other two are optimizations which try to use trees (kd_tree), and spheres(ball_tree) to speed up this algo, but to start let's just do brute.