Manhattan distance

This term describes a specific metric used in mathematics and computer science, often referred to as taxicab geometry. It reflects a grid-like movement where diagonal travel is prohibited, mirroring how a vehicle must navigate the perpendicular streets of Manhattan. This creates a distinct contrast with Euclidean distance, which measures the straight-line "as the crow flies" path.

In practical application, it is frequently employed in machine learning and data science, particularly in algorithms like k-nearest neighbors when dealing with discrete or integer-based features. Because it sums absolute differences rather than squaring them, it is less sensitive to extreme outliers than the Euclidean metric.