Manhattan distance, also known as L1 distance or taxicab geometry, measures the distance between two points in a grid-based path by summing the absolute differences of their Cartesian coordinates. It is particularly useful in scenarios where movement is restricted to horizontal and vertical paths, such as grid-based maps or certain machine learning algorithms.