The Unique Games problem is the following: we are given a graph G = (V,E), with each edge e = (u,v) having a weight we and a permutation πuv on [k]. The objective is to find a labeling of each vertex u with a label fu ∈ [k] to minimize the weight of unsatisfied edges—where an edge (u,v) is satisfied if fv = πuv(fu). The Unique Games Conjecture of Khot [8] essentially says that for each ε > 0, there is a k such that it is NP-hard to distinguish instances of Unique games with (1−ε) satisfiable edges from those with only ε satisfiable edges. Several hardness results have recently been proved based on this assumption, including optimal ones for Max-Cut, Vertex-Cover and other problems, making it an important challenge to prove or refute the conjecture. In this paper, we give an O(logn)-approximation algorithm for the problem of minimizing the number of unsatisfied edges in any Unique game. Previous results of Khot [8] and Trevisan [12] imply that if the optimal solution has OPT = εm unsatisfied edges, semidefinite relaxations of the problem could give labelings with min{k2ε1/5,(εlogn)1/2}m unsatisfied edges. In this paper we show how to round a LP relaxation to get an O(logn)-approximation to the problem; i.e., to find a labeling with only O(εmlogn) = O(OPTlogn) unsatisfied edges.