Identifying fishing spots is vital for sustainable fisheries management, conservation, and optimizing fishing activities. This paper provides a comprehensive review of Artificial Intelligence, Machine Learning, Big Data, and Data Analytics in enhancing fishing spot detection, surpassing the limitations of traditional methods such as fisher experience and historical catch data. These advanced approaches improve accuracy in locating productive fishing areas by integrating remote sensing, Geographic Information Systems, and real-time data from sonar and satellite imagery. The study emphasizes the role of environmental factors—such as water temperature, salinity, and ocean currents—in influencing fish distribution and explores the impact of technological advancements on eco-friendly fishing practices. Current challenges include data availability, environmental variability, and the need for interdisciplinary collaboration. Additionally, the paper outlines the transformative potential of these technologies to optimize resource utilization and preserve marine ecosystems, suggesting future research directions to address existing gaps. As these methods continue to evolve, their wider adoption is expected to support the sustainability of fisheries and environmental conservation significantly.