Distance matrix completion involves estimating missing values in a partially observed distance matrix, enabling the reconstruction of geometric or structural information essential for applications such as network topology and molecular conformation. The challenge lies in leveraging constraints like triangle inequalities and additional domain knowledge to accurately infer these missing distances.