K-Nearest Neighbors (KNN) is a fundamental supervised machine learning algorithm used for classification and regression tasks. It operates on the principle of identifying the ‘k’ closest data points, or neighbors, in the feature space to make predictions about a new data point. The algorithm is intuitive and easy to understand, as it simply memorizes the training data without any complex modeling. When a new instance is introduced, KNN classifies it based on the majority class among its nearest neighbors or calculates the average for regression tasks. This simplicity makes KNN a popular choice for various applications in data science.