While artificial intelligence (AI) promises transformative societal benefits, it also presents significant challenges in ensuring equitable access and value for the Global Majority. Building on emerging research on algorithmic reparations, algorithmic impact assessments, and participatory AI, this paper introduces Reparative Algorithmic Impact Assessments (R-AIAs)—a novel framework that combines robust accountability mechanisms with a reparative praxis to form a more culturally sensitive, justice-oriented methodology. By further incorporating decolonial, Intersectional principles, R-AIAs move beyond merely centering diverse perspectives and avoiding harm to actively redressing historical, structural, and systemic inequities. This includes colonial legacies and their algorithmic manifestations. Using the example of an AI-powered mental health chatbot in rural India, we explore concrete strategies through which R-AIAs can achieve these objectives, fostering equity for the Global Majority in the process.