K-nearest neighbors is a simple machine learning algorithm that classifies a new data point by looking at the k most similar examples already seen and adopting their majority label. No real training happens: the algorithm just memorizes the data and compares distances. Think of pricing a riad in Marrakech by checking the five most similar riads recently sold nearby and averaging their prices. KNN is intuitive and effective on small datasets, but slows down considerably as data volume grows.