According to the dual inheritance theory, human behavior is a result of genetic as well as cultural evolution. The socio-
cultural inspired algorithms are developed by observing human behavior in a society. These social interactions contribute to the progress of humanity. This class of algorithms simulates various social setups like an election, a sports championship, an imperialistic colony, a family, or a group of friends who help other members in the group to improve their behavior while fulfilling their own goals. Some setups show a cooperative nature while others exhibit the competitive nature of humans. Like other Evolutionary algorithms, Social algorithms too are based on the principle of ‘survival of the fittest’ and are metaheuristics used for optimization problems. This work is aimed to give a brief overview of 15 Social algorithms with their advantages, limitations, and applications solved, so as to provide a succinct, yet comprehensive, outline of these techniques.