Individual daily mobility exhibits a striking scaling law: the probability of returning home after a tour of locations decays as . While the tour-terminate-continue (TTC) model reproduces this behavior, it relies on this power law as an empirical input, leaving the microscopic origin of unresolved. Here we show that this scaling emerges from a utility trade-off governed by cognitive constraints. By invoking the principle of least effort, we demonstrate that individual activity priorities follow Zipf's law, , which directly dictates the sublinear accumulation of tour utility, . Luce's choice rule then yields , giving the exact exponent . Agent-based simulations confirm this analytical relation. Our framework bridges the gap between individual cognitive constraints and the scaling law of tour behavior, providing a microscopic theoretical underpinning for human mobility.