I'm using plotCounts(ddsM14.5, gene = "Bmp7", intgroup=c("Region")) to find expression of Bmp7 in each sample. I have 3 repeats for each region and I want to identify which sample the outlier is from. Can I colour or label the point by the colname?

You could use ggplot2 (you do not provided data so I cannot test) :

plot = plotCounts(ddsM14.5, gene = "Bmp7", intgroup=c("Region"))

ggplot(plot, aes(x = Region, y = count, color = Region)) + 
  geom_point()

You can return the data (rather than extracting manually from dds which is not difficult though) and then do ggplot "magic":

library(DESeq2)
library(ggplot2)
library(ggrepel)

dds <- makeExampleDESeqDataSet()
dds <- estimateSizeFactors(dds)

data <- plotCounts(dds, gene = "gene1", intgroup=c("condition"), returnData=TRUE)
data$sample <- rownames(data)

# Here using log2 of the counts, many options in ggplot to do axis scaling in case span of counts is large, please take a ggplot tutorial
ggplot(data=data, aes(x=condition, y=log2(count+1), label=sample)) +
  geom_point() +
  geom_label_repel(min.segment.length=0, max.overlaps=Inf)