Attribute filtering is a data processing technique used to select relevant features or attributes from a dataset, enhancing the performance and efficiency of machine learning models. By eliminating irrelevant or redundant data, attribute filtering helps in reducing the dimensionality and complexity of the data, leading to improved model interpretability and accuracy.