CO₂ capture and sequestration is a prominent field of study with high research demands. It involves capturing CO₂ from various large point sources and storing it to prevent its emission. Various conventional CO₂ sequestration techniques currently in practice involve CO₂ storage in geological formations such as depleted oil and gas reservoirs, saline aquifers, and enhanced oil recovery (EOR) applications. Another emerging technique is to store CO₂ in the hydrate form in marine sediments owing to its large storage capacity. Gas hydrates are crystalline solid structures formed by the physical combination of gas (such as methane, carbon dioxide, propane, etc.) and water molecules at high-pressure and low-temperature conditions. This chapter briefly describes the conventional CO₂ sequestration techniques with the challenges encountered in their application. Further, the chapter discusses the use of machine learning in gas hydrate related studies particularly concerning hydrate-based CO₂ capture and sequestration.