In their seminal paper introducing the theory of random graphs, Erdős and Rényi considered the evolution of the structure of a random subgraph of $K_n$ as the density increases from $0$ to $1$, identifying two key points in this evolution -- the \emph{percolation threshold}, where the order of the largest component seemingly jumps from logarithmic to linear in size, and the \emph{connectivity threshold}, where the subgraph becomes connected. Similar phenomena have been observed in many other random graph models, and in particular, works of Ajtai, Komlós and Szemerédi and of Spencer and Erdős determine corresponding thresholds for random subgraphs of the hypercube. We study similar questions on the \emph{permutahedron}. The permutahedron, like the hypercube, has many different equivalent representations, and arises as a natural object of study in many areas of combinatorics. In particular, as a highly-symmetric simple polytope, like the $n$-simplex and $n$-cube, this percolation model naturally generalises the Erdős-Rényi random graph and the percolated hypercube. We determine the percolation threshold and the connectivity threshold for random subgraphs of the permutahedron. Along the way we develop a novel graph exploration technique which can be used to find exponentially large clusters after percolation in high-dimensional geometric graphs and we initiate the study of the isoperimetric properties of the permutahedron.