Marine pollution is a pressing environmental issue with profound implications for ecosystems, biodiversity, and human livelihood. This chapter delves into the transformative role of hyperspectral imaging in monitoring and mitigating pollution in marine environments. Pollutants such as oil spills and plastics are particularly impactful, causing severe damage in the short term or remaining persistently in the marine environment. Hyperspectral images provide unparalleled precision in detecting these contaminants by capturing detailed spectral information across hundreds of narrow bands. The chapter introduces key advancements, including specialised spectral indices that allow real-time detection. Band selection methodologies are highlighted as tools to identify the most relevant spectral features, improve pollutant classification, and facilitate machine learning (ML) model transfer across diverse environments. Emerging technologies, such as specialised multispectral sensors integrated into cost-effective platforms like CubeSats, demonstrate the potential for scalable environmental monitoring. Additionally, cloud computing platforms enable efficient processing of vast datasets, enhancing the global accessibility of hyperspectral imaging (HSI) solutions. While these innovations address critical challenges in data complexity and model generalisation, the chapter underscores the need for interdisciplinary collaboration to refine these methods and integrate them into policy frameworks. These tools offer a path towards more effective marine pollution management and ocean stewardship.