The K-Nearest Neighbors (KNN) algorithm is a supervised machine learning algorithm used for classification and regression tasks. In the KNN algorithm, a new data point is classified based on the class of its nearest neighbors in the training set.

The KNN classifier assigns a class to a data point by finding the k nearest neighbors in the training set, where k is a user-defined parameter. A majority vote of the k nearest neighbors then determines the class of the new data point.

The KNN algorithm is simple and flexible but computationally expensive for large datasets. It also requires careful selection of the k value and distance metric. KNN is a useful and widely-used algorithm for classification tasks in machine learning.