The smoothness constraint is a principle used in various fields, such as computer vision and numerical analysis, to ensure that solutions or models change gradually rather than abruptly. It helps in reducing noise and improving the stability of algorithms by enforcing a preference for solutions with minimal variations between neighboring points or elements.