K-nearest neighbors (KNN) is a nonparametric, instance-based learning algorithm used for classification and regression tasks that operates by identifying the 'k' closest data points in the feature space to make predictions. This method relies on the distance between points and is particularly useful in nonparametric density estimation, where it helps to estimate the probability density function of a random variable by evaluating the distribution of data points in relation to their neighbors.
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