I missed the programmatic workflow of Python, so I decided to switch back to Python for this Algorithm. Also, please note that the K Nearest Neighbor can be found and implemented quickly in Scikit-learn, but I wanted to code it from scratch. I discovered the K Nearest Neighbor when I was exploring other simple machine algorithms. Initially, I mistook this algorithm to be a close relative of the K means algorithm.
The main difference lies is that the K Nearest Neighbor (KNN) is a supervised classification whereas the K means algorithm is unsupervised with a hint of grouping by clustering. How's it work? The KNN functions by taking a number (k) of points in proximity, surrounding an unclassified point and relies on the classification by selecting the majority winner.