K-Nearest Neighbors (KNN) is a lazy learning algorithm that classifies or regresses a sample based on the labels of its nearest neighbors in feature space. It requires no explicit training but can be computationally expensive for large datasets at inference time. The choice of K and distance metric significantly affects performance.