A distance metric is a mathematical function that quantifies the distance between two points in a given space. It is commonly used in various fields such as machine learning, statistics, and geometry to measure similarity or dissimilarity between data points. Common examples of distance metrics include Euclidean distance, which calculates the straight-line distance, and Manhattan distance, which measures distance along axes at right angles. Distance metrics help in clustering, classification, and other analytical tasks by providing a way to compare data points. By using these metrics, algorithms can group similar items together or identify outliers. Understanding distance metrics is essential for effective data analysis and interpretation.