Machine Learning is the study of computer algorithms that can improve automatically through experience and by the use of data. The complex mathematical expressions of physical processes of floods, during the past two decades can be studied through Machine Learning and these methods have contributed highly in the advancement of prediction systems providing better performance and cost-effective solutions. Due to the vast benefits and potential of Machine Learning, it is heavily popular among hydrologists. Researchers through introducing novel Machine Learning methods and hybridizing of the existing ones aim at discovering more accurate and efficient prediction models. Flooding is the most devastating natural hazard in Pakistan and the recently flooding has demonstrated its severeness through large scale destruction and displacement of homes and businesses in Interior Sindh. This paper aims to explore the methodologies of flood detection currently used in Pakistan, and the potential of Machine Learning in prediction systems within the country. Drawing on sources such as journals, scientific articles, and websites, the research assembled relevant information concerning floods and their prevention.