Earth Mover's Distance (EMD) is a measure used to compare two probability distributions. It calculates the minimum cost required to transform one distribution into another by moving "earth" (or mass) from one location to another. This concept is particularly useful in fields like computer vision and image retrieval, where it helps assess the similarity between different images. EMD is based on the idea of optimal transport, which finds the most efficient way to move resources. By considering both the amount of distribution and the distance between points, EMD provides a more intuitive comparison than traditional metrics, making it valuable for applications in machine learning and data analysis.