Algorithmic governance is transforming the way decisions are made, rules are enforced, and behavior is regulated. Unlike traditional modes of governance that rely on hierarchical authority or market mechanisms, algorithmic governance operates through data-driven, automated systems that dynamically shape societal interactions. This chapter argues that based on the unique characteristics of algorithmic governance make it fundamental evolution in the modes of governance. Thus, algorithmic governance does not simply fit within existing governance typologies but represents a distinct and evolving paradigm with profound implications for policy, regulation, and societal organization. While algorithms enhance efficiency and scalability, they also introduce challenges related to transparency, accountability, and fairness. By examining three cases, this chapter highlights both the promises and risks associated with algorithmic governance. It underscores the need for a human-centered approach that balances technological innovation with ethical considerations. As algorithms continue to mediate power and decision-making, it becomes essential to develop governance frameworks that ensure accountability, safeguard democratic values, and protect individual rights in an increasingly automated world.