As the hyperspectral image consists of hundreds of highly correlated spectral bands, the selection of informative and highly discriminative bands is necessary for hyperspectral image classification. The recent growth of machine learning and artificial intelligence techniques play a major role in various domains of hyperspectral image processing. In this paper, a comprehensive survey of machine learning and artificial intelligence technique-based band selection strategies for hyperspectral image classification is given. As per the outcome of this study, we have identified the research challenges and research for future directions in band selection strategies for hyperspectral image classification.