Earth Mover's Distance (EMD) is a measure of the distance between two probability distributions over a region, which essentially quantifies the minimum amount of 'work' required to transform one distribution into the other. It is particularly useful in comparing multi-dimensional distributions in fields such as image processing, computer vision, and machine learning, where it provides a more nuanced comparison than simpler metrics.