I think this question somewhat comes down to what "camp" of DFT progression you subscribe to. I should specify upfront that this summary is mainly centered around molecular systems, so some of the recommendations likely vary for materials where the computational workload can often be much greater.
One side really emphasizes accuracy with respect to experiment and is somewhat less concerned with the physical interpretation of the functional form. These groups make efforts to directly improve the accuracy of functionals with respect to experiment by extensive fitting and parameterization. Some functionals that fit into this category would be the Minnesota Functionals from the Truhlar group, as well the ωB97X and ωB97M functionals from the Head-Gordon group. Based on fairly extensive benchmarking (see this excellent paper), these functionals are tough to beat for a wide variety of energetic metrics and types of molecules.
On the other side, the form of functionals is more physically motivated. This is done by ensuring the functional satisfies certain exact constraints of the "universal functional". A prominent example of this type is the SCAN functional from Perdew et al. While these types of functionals have not been able to achieve the same experimental accuracy as more heavily parameterized functionals, there is a chance that they are more robust and amenable to improvement, as they exactly match known properties of the "universal functional".
So it depends in what you are interested. If you want the closest functional form to the "universal functional", you would likely want something from the second camp. However, if your interest is in what will give you the best results for a wide range of complexes/materials right now, you will likely want to go with a functional that has been extensively parameterized on a large training set.