Nearest neighbors is a type of instance-based learning used in machine learning and statistics where the classification or prediction of a data point is based on the closest data points in the feature space. It is highly effective for non-linear data and requires no prior assumptions about the distribution of data, but can struggle with high-dimensional data and computational efficiency as the dataset size increases.