A subset $A$ of a vector space $V$ is called affine if it satisfies any of the following equivalent conditions:
- There is a $p \in A$ such that the set $A - p := \{v -p\mid v \in A\}$ is a vector subspace of $V$.
- For every $p \in A$, the set $A - p$ is a vector subspace of $V$.
- For every pair of points $p, q \in A$ and $t$ in the field of $V$, $tp + (1-t)q \in A$. That is, if $A$ contains two points, it also contains the line running through them.
You could develop the concept of "affine" without reference to a vector space. Euclid did that for real affine spaces of 1, 2, and 3 dimensions over two thousand years ago. He called them "lines", "planes" and "space", respectively. But generally, it is nicer to have a ready-made linear structure built-in instead of having to create one from a bunch of geometric axioms.
Note that any vector space is automatically affine. More generally if $U$ is subspace of $V$ and $p \in V$, then $U + p$ is an affine space.
There is no such thing as a "normed affine space", as "norm" refers to the distance from a point to the origin, and affine spaces do not contain an origin or any other distinguished point. There is no property of the affine space itself that will differentiate between two points within it. The only way to identify a specific point in an affine space is by reference to the containing vector space. However, if the vector space $V$ has a norm, then there is a metric on any affine subspace, measuring the distance between any two points in the affine space.