The importance of materials in our life is well known to the world. Material science is one of the crucial research domain which deals with planning, development, synthesis and analysis of materials and its use in the real applications. The scientists and researcher are using highly advance technologies for the production and design of new materials in present era; however the process is time consuming. Machine Learning can be defined as a set of techniques that learn from the large amount of available data and make predictions for the new data. Recently, machine learning has gained a great attraction in material science research and has been used in several research studies. Machine learning techniques have the potential to learn from the large amount of materials data and make predictions about different properties for new materials of good quality. These predictions can help in designing new materials. In this paper, we present a comprehensive review on the machine learning applications in different material science domain. We believe that the paper would be useful for the researchers, academicians and students who are involved in the design of new materials.