K-Nearest Neighbors

K-Nearest Neighbors (KNN) is a simple, yet powerful, supervised machine learning algorithm used for classification and regression tasks. It operates on the principle that similar data points are located close to each other in the feature space. The algorithm identifies the 'k' closest training examples to a new input and makes predictions based on the majority class (for classification) or the average (for regression) of these neighbors. KNN is particularly popular due to its ease of implementation and effectiveness in low-dimensional spaces, making it a common choice for tasks such as image recognition and recommendation systems.