The K-nearest neighbors (KNN) algorithm is a simple and widely-used machine learning algorithm primarily used for classification and regression tasks. It is a type of instance-based learning, meaning it makes predictions based on the instances (data points) that are stored in the training set. ### Key Concepts: 1. **Instance-based learning**: KNN stores all of the training instances and makes decisions based on the instances it finds most similar to new data.

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One of the most simply classification algorithm one can think of: just see whatever kind of point your new point seems to be closer to, and say it is also of that type! Then it is just a question of defining "close".