Climate change is one of the greatest problems society has ever faced, with increasingly severe consequences for humanity as natural disasters multiply, sea levels rise, and ecosystems falter. While climate change is a truly global problem, it manifests itself via many local effects, which pose unique problems and require corresponding actions. These actions can take many forms, from designing smart electric grids to tracking greenhouse gas emissions through satellite imagery. While no silver bullet, machine learning can be an invaluable tool in fighting climate change via a wide array of applications and techniques. These applications require algorithmic innovations in machine learning and close collaboration with diverse fields and practitioners. This workshop is intended as a forum for those in the global machine learning community who wish to help tackle climate change, and is further aimed to help foster cross-pollination between researchers in machine learning and experts in complementary climate-relevant fields. Building on our past workshops on this topic, this workshop particularly aims to explore the connection between global perspectives and local challenges in the context of applying machine learning towards tackling climate change. We want to take the opportunity of the first leading machine learning conference being hosted in person in a non-Western country to shine a light on work that deploys, analyzes or critiques ML methods and their use for climate change adaptation and mitigation in low-income countries.